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Related Experiment Video

Updated: Jun 24, 2025

The Automated Crystallography Pipelines at the EMBL HTX Facility in Grenoble

The Automated Crystallography Pipelines at the EMBL HTX Facility in Grenoble

Published on: June 5, 2021

Using EMBL-EBI Services via Web Interface and Programmatically via Web Services.

Fábio Madeira¹, Nandana Madhusoodanan¹, Joonheung Lee¹

¹European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.

Current Protocols

|June 10, 2024

Summary

This summary is machine-generated.

The European Bioinformatics Institute (EMBL-EBI) offers web services and Docker containers for accessing bioinformatics databases and tools. Researchers can integrate these resources into workflows using clients in Perl, Python, and Java.

Keywords:

REST SOAP bioinformatics resources bioinformatics tools programmatic access web services workflows

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Area of Science:

Bioinformatics
Computational Biology
Data Science

Background:

The European Bioinformatics Institute (EMBL-EBI) provides critical bioinformatics databases and analysis tools.
Programmatic access to these resources is essential for integrating them into analytical workflows and pipelines.
Web services (REST and SOAP) and containerization (Docker) offer flexible integration options.

Purpose of the Study:

To describe the methods and options for accessing EMBL-EBI resources programmatically.
To guide researchers and bioinformaticians in utilizing web services and Docker containers for bioinformatics analyses.
To facilitate the integration of EMBL-EBI tools into custom analytical pipelines.

Main Methods:

Utilizing RESTful web services clients in Perl, Python, and Java for data retrieval and analysis.
Employing Docker containers for seamless integration of EMBL-EBI resources into analysis workflows.
Demonstrating specific protocols for data retrieval (Dbfetch), sequence similarity search (FASTA, BLAST+, HMMER3), protein functional analysis (InterProScan 5), and multiple sequence alignment (Clustal Omega).

Main Results:

Successful programmatic access to EMBL-EBI resources is demonstrated through various clients and protocols.
Integration of core bioinformatics tools into analysis pipelines is achievable using provided methods.
The article serves as a practical guide with detailed protocols for diverse bioinformatics tasks.

Conclusions:

EMBL-EBI resources are readily accessible and integrable into computational workflows via web services and Docker.
Researchers can leverage these tools to enhance their bioinformatics analyses and data processing capabilities.
The described methods empower bioinformaticians to build robust and reproducible analysis pipelines.